Understanding process behaviours in a large insurance company in Australia : a case study

Having a reliable understanding about the behaviours, problems, and performance of existing processes is important in enabling a targeted process improvement initiative. Recently, there has been an increase in the application of innovative process mining techniques to facilitate evidence-based understanding about organizations' business processes. Nevertheless, the application of these techniques in the domain of finance in Australia is, at best, scarce. This paper details a 6-month case study on the application of process mining in one of the largest insurance companies in Australia. In particular, the challenges encountered, the lessons learned, and the results obtained from this case study are detailed. Through this case study, we not only validated existing `lessons learned' from other similar case studies, but also added new insights that can be beneficial to other practitioners in applying process mining in their respective fields.

Insurance and transport law : controlling insurance contract terms : Section 54 of the Insurance Contracts Act – compliance, recovery and accountability

Commonwealth legislation covering insurance contracts contains numerous provisions designed to control the operation and effect of terms in life and general insurance contracts. For example, the Life Insurance Act 1995 (Cth) contains provisions regulating the consequences attendant upon incorrect statements in proposals [1] and non-payment of premiums, [2] provides that an insurer may only exclude liability in the case of suicide if it has made express provision for such contingency in its policy, [3] and severely restricts the efficacy of conditions as to war risks. [4] The Insurance Contracts Act 1984 (Cth) is even more intrusive and has a major impact upon contractual provisions in the general insurance field. It is beyond the scope of this note to explore all of these provisions in any detail but examples of controls and constraints imposed upon the operation and effect of contractual provisions include the following. A party is precluded from relying upon a provision in a contract of insurance if such reliance would amount to a failure to act with the utmost good faith. [5] Similarly, a policy provision which requires differences or disputes arising out of the insurance to be submitted to arbitration is void, [6] unless the insurance is a genuine cover for excess of loss over and above another specified insurance. [7] Similarly clause such as conciliation clauses, [8] average clauses, [9] and unusual terms [10] are given qualified operation. [11] However the provision in the Insurance Contracts Act that has the greatest impact upon, and application to, a wide range of insurance clauses and claims is s 54. This section has already generated a significant volume of case law and is the focus of this note. In particular this note examines two recent cases. The first, Johnson v Triple C Furniture and Electrical Pty Ltd [2012] 2 Qd R 337, (hereafter the Triple C case), is a decision of the Queensland Court of Appeal; and the second, Matthew Maxwell v Highway Hauliers Pty Ltd [2013] WASCA 115, (hereafter the Highway Hauliers case), is a decision of the Court of Appeal in Western Australia. This latter decision is on appeal to the High Court of Australia. The note considers too the decision of the New South Wales Court of Appeal in Prepaid Services Pty Ltd v Atradius Credit Insurance NV [2013] NSWCA 252 (hereafter the Prepaid Services case).These cases serve to highlight the complex nature of s 54 and its application, as well as the difficulty in achieving a balance between an insurer and an insured's reasonable expectations.

A recommendation system for predicting risks across multiple business process instances

This paper proposes a recommendation system that supports process participants in taking risk-informed decisions, with the goal of reducing risks that may arise during process execution. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a business process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we suggest to the participant the action to perform which minimizes the predicted process risk. Risks are predicted by traversing decision trees generated from the logs of past process executions, which consider process data, involved resources, task durations and other information elements like task frequencies. When applied in the context of multiple process instances running concurrently, a second technique is employed that uses integer linear programming to compute the optimal assignment of resources to tasks to be performed, in order to deal with the interplay between risks relative to different instances. The recommendation system has been implemented as a set of components on top of the YAWL BPM system and its effectiveness has been evaluated using a real-life scenario, in collaboration with risk analysts of a large insurance company. The results, based on a simulation of the real-life scenario and its comparison with the event data provided by the company, show that the process instances executed concurrently complete with significantly fewer faults and with lower fault severities, when the recommendations provided by our recommendation system are taken into account.

Factors influencing vulnerability and positive post-disaster response following the Mackay 2008 and Brisbane 2011 floods

This project investigated which aspects of being flooded most affected mental health outcomes. It found that stress in the aftermath of the flood, during the clean-up and rebuilding phase, including stress due to difficulties with insurance companies, was a previously overlooked risk factor, and social support and sense of belonging were the strongest protective factors. Implications for community recovery following disasters include providing effective targeting of support services throughout the lengthy rebuilding phase; the need to co-ordinate tradespeople; and training for insurance company staff aimed at minimising the incidence of insurance company staff inadvertently adding to disaster victims' stress.

Marketing to change public opinion on climate change : a case study

Corporate advertisers spend far greater budgets than any social marketing campaign and have great potential to change public opinion on the urgent need for action on climate change. However “green-washing” has become a widespread practice by companies that wish to appear to be socially responsible without a genuine commitment and consumers can be very cynical about green marketing campaigns. Can companies be climate change advocates and still satisfy shareholders? This paper offers a case study on an Australian insurance company that argues it can make money from doing the right thing.

Applying data mining to assess crash risk on curves

The wide range of contributing factors and circumstances surrounding crashes on road curves suggest that no single intervention can prevent these crashes. This paper presents a novel methodology, based on data mining techniques, to identify contributing factors and the relationship between them. It identifies contributing factors that influence the risk of a crash. Incident records, described using free text, from a large insurance company were analysed with rough set theory. Rough set theory was used to discover dependencies among data, and reasons using the vague, uncertain and imprecise information that characterised the insurance dataset. The results show that male drivers, who are between 50 and 59 years old, driving during evening peak hours are involved with a collision, had a lowest crash risk. Drivers between 25 and 29 years old, driving from around midnight to 6 am and in a new car has the highest risk. The analysis of the most significant contributing factors on curves suggests that drivers with driving experience of 25 to 42 years, who are driving a new vehicle have the highest crash cost risk, characterised by the vehicle running off the road and hitting a tree. This research complements existing statistically based tools approach to analyse road crashes. Our data mining approach is supported with proven theory and will allow road safety practitioners to effectively understand the dependencies between contributing factors and the crash type with the view to designing tailored countermeasures.

Mining patterns and factors contributing to crash severity on road curves

Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

Business Process Model Merging : An Approach to Business Process Consolidation

This paper addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The paper considers the construction of unions of multiple models (called merged models) as well as intersections (called digests). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models - typically representing variants of the same underlying process - with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The paper presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.

The extent of the insured’s duty of disclosure : a comparative analysis of the disclosure obligations of insured in Australia, Singapore and China

Pre-contractual material disclosure and representation from an insurance policy proposer is the most important element for insurers to make a decision on whether a proposer is insurable and what are the terms and conditions if the proposal by the proposer is able to be insured. The issue this thesis researches and investigates focus on the issues related to the pre-contractual non-disclosures and misrepresentations of an insured under the principle of utmost good faith, by operation of laws, can achieve with different results in different jurisdiction. A similar disputed claim involving material non-disclosed personal information or misrepresentation at the pre-contractual stage from an insured with respect to both general and life insurance policies settled by an insurer in Australia could be that the policy is set aside ab initio by the insurers in Singapore or China. The jurisdictions this thesis examines are • Australia; • Singapore; and • China including Hong Kong.

Profiling event logs to configure risk indicators for process delays

Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators(PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.

Practice and procedure - Disclosure of documents - application of UCPR r222 to documents referred to in exhibit to affidavit

In Century Drilling Limited v Gerling Australia Insurance Company Pty Limited [2004] QSC 120 Holmes J considered the application of a number of significant rules impacting on the obligation to disclose under the Uniform Civil Procedure Rules 1999

Stress during the rebuilding phase influenced mental health following two Queensland flood disasters more than the event itself

It has long been known that disasters can have mental health consequences such as increased rates of PTSD, depression and anxiety. While some research has shown that secondary stressors during the aftermath of a disaster can influence psychological outcomes, this aspect of the disaster experience has not been widely studied. This paper reports on two studies that investigated which aspects of the experience of being flooded were most predictive of mental health outcomes. The first study was a qualitative study of adults whose homes had been inundated in the Mackay flood of 2008 (n=16). Thematic analysis of interviews conducted 18-20 months post-flood found that stressors during the flood aftermath such as difficulties and delays during the rebuilding process and a difficult experience with an insurance company were nominated as the most stressful aspect of the flood by the majority of participants. The second study surveyed Mackay flood survivors three and a half years post-flood, and Brisbane 2011 flood survivors 7-9 months post-flood (n=158). Findings indicated aftermath stress contributed to mental health outcomes over and above the contribution of perceived trauma, objective flood severity, prior mental health, self-efficacy and demographic factors. The implications of these results for the provision of community recovery services following natural disasters are discussed, including the need to provide effective targeting of support services throughout the lengthy rebuilding phase; a possible role for co-ordinating tradespeople; and training for insurance company staff aimed at minimising the incidence of insurance company staff inadvertently adding to disaster victims’ stress.

Insurance : The Laws of Australia

Insurance - the laws of Australia provides insurance practitioners, insurance companies and students with a principles-based, practical guide to insurance law in Australia. It provides comprehensive coverage and analysis of common law principles relating to, and the statutory regulation of, insurance contracts and the operation of an insurance business. The common law and statutory provisions are dealt within the context of marine, life and general insurance.